Three-mode partitioning

DOI10.1016/j.csda.2006.06.002zbMath1157.62447OpenAlexW1972109943MaRDI QIDQ1010515

Iven van Mechelen, Jan Schepers, Eva Ceulemans

Publication date: 6 April 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2006.06.002

zbMATH Keywords

clustering\(k\)-meansthree-way dataalternating least-squares algorithms

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items

Maximal interaction two-mode clustering, Discovering patterns in time-varying graphs: a triclustering approach, Deriving optimal data-analytic regimes from benchmarking studies, One mode three-way overlapping cluster analysis, CLASSI: A classification model for the study of sequential processes and individual differences therein, Selecting among multi-mode partitioning models of different complexities: a comparison of four model selection criteria, A unifying model involving a categorical and/or dimensional reduction for multimode data, Block-relaxation approaches for fitting the INDCLUS model

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Optimising \(k\)-means clustering results with standard software packages
• Differential evolution and particle swarm optimisation in partitional clustering
• Principal component analysis of three-mode data by means of alternating least squares algorithms
• An alternating combinatorial optimization approach to fitting the INDCLUS and generalized INDCLUS models
• Probabilistic models in cluster analysis
• A classification EM algorithm for clustering and two stochastic versions
• Combinatorial Data Analysis
• K-Means-Type Algorithms: A Generalized Convergence Theorem and Characterization of Local Optimality
• Asymptotic behaviour of classification maximum likelihood estimates
• Model-Based Gaussian and Non-Gaussian Clustering
• Two-mode clustering methods: astructuredoverview